A chart or graph is described in Wikipedia as a type of information graphic or graphic organizer that represents tabular numeric data and/or functions. Charts are often used to make it easier to understand large quantities of data and the relationship between different parts of the data. Charts can usually be read more quickly than the raw data that they come from. They are used in a wide variety of fields, and can be created by hand (often on graph paper) or by computer using a charting application.
Traditional charts use well established and often poorly implemented ways of representing data. Many tools exist to help the user construct very sophisticated representations of data but that sophistication typically results in less meaningful charts. Embodiments of the present invention aim to overcome this problem.
It is known to use charting wizards such as those that are available in Excel and various other systems such as those provided by, for example, IBM. In addition there are multiple Business Intelligence (BI) tools available to users to enable users to analyze data in an attempt to create meaningful feedback. However, as the amount of data increases, so does the complexity of the visual representations created by the analysis of the data. These complex representations can end up swamping parts of the visual representation that is most required and relevant to an end user, particularly in cases where high dimensional data is visually represented.
Further, the focus of existing known methods of graphically representing data is on providing a single visual design, or type of visual design or visual representation, to represent data. That is, to produce, for example, a single bar graph to be displayed, or a single pie chart to be printed. This is very limiting to a user who may want to show various different aspects of the data in a single document.
Further, due to the inherent problems associated with systems that attempt to visualize high dimensional data and particularly large volumes of high dimensional data, different visualization methods have been suggested to overcome these problems. Most of these methods use latent variables (such as principal component analysis) to reduce the dimensionality of the data to 2 or 3 dimensions before plotting the data. One problem with this approach is that the latent variables sometimes are hard to understand in terms of the original variables and so the user is not able to efficiently analyze the visualized results.
The parallel coordinate (PC) scheme due to Inselberg and others attempts to plot multivariate data in a completely different manner by transforming high dimensional information into a two dimensional representation using a number of parallel lines to represent each dimension. Since plotting more than 3 orthogonal axis is impossible, parallel coordinate schemes plot all the axes parallel to each other in a plane. Squashing the space in this manner does not destroy too much of the geometric structure. The geometric structure is however projected in such a fashion that most geometric intuition has to be relearned, this is a significant drawback, particularly for visualization of business data.
The present invention aims to overcome, or at least alleviate, some or all of the mentioned problems, or to at least provide the public with a useful choice.